"""
This module provides test matrix generation functionality for creating parameterized test cases.

The module supports two generation modes:
- AETG (Automatic Efficient Test Generator): Generates test cases using combinatorial testing
- MATRIX: Generates full Cartesian product of all parameter combinations

It is designed to work seamlessly with pytest's parametrize decorator for creating comprehensive
test suites with reduced test case counts while maintaining coverage.
"""

from enum import IntEnum, auto
from typing import List, Mapping, Union, Tuple, Optional

from .aetg import AETGGenerator
from .matrix import MatrixGenerator
from ...model import int_enum_loads
from ...reflection import progressive_for

__all__ = ['tmatrix']


@int_enum_loads(enable_int=False, name_preprocess=str.upper)
class MatrixMode(IntEnum):
    """
    Enumeration of matrix generation modes.

    :cvar AETG: AETG (Automatic Efficient Test Generator) mode for combinatorial testing
    :cvar MATRIX: Full Cartesian product matrix mode
    """
    AETG = auto()
    MATRIX = auto()


def tmatrix(ranges: Mapping[Union[str, Tuple[str, ...]], List],
            mode='aetg', seed: Optional[int] = 0, level: int = 2) -> Tuple[List[str], List[Tuple]]:
    """
    Generate test matrix for parameterized testing.

    This function creates a test matrix that can be directly used with pytest's parametrize
    decorator. It supports two generation modes: AETG for efficient combinatorial testing
    and MATRIX for full Cartesian product generation.

    :param ranges: Mapping of parameter names to their possible values. Keys can be either
                   a single string (for one parameter) or a tuple of strings (for multiple
                   parameters that should be varied together). Values are lists of possible
                   values for the parameter(s).
    :type ranges: Mapping[Union[str, Tuple[str, ...]], List]
    :param mode: Generation mode, should be either 'aetg' or 'matrix'. Default is 'aetg'.
    :type mode: str
    :param seed: Random seed for AETG mode. Default is 0 which produces deterministic results.
                 Set to None for non-deterministic generation.
    :type seed: Optional[int]
    :param level: Coverage level for AETG algorithm, indicating the strength of combinatorial
                  coverage (e.g., 2 for pairwise coverage). Default is 2.
    :type level: int

    :return: A tuple containing (parameter_names, test_cases) where parameter_names is a list
             of parameter names and test_cases is a list of tuples, each representing one test case.
    :rtype: Tuple[List[str], List[Tuple]]
    :raises ValueError: If an invalid mode is specified.

    Examples::
        >>> from hbutils.testing import tmatrix
        >>> names, values = tmatrix(
        ...     {
        ...         'a': [2, 3],
        ...         'e': ['a', 'b', 'c'],
        ...         ('b', 'c'): [(1, 7), (4, 6), (9, 12)],
        ...     }
        ... )
        >>> print(names)
        ['a', 'e', 'b', 'c']
        >>> for i, v in enumerate(values):
        ...     print(i, v)
        0 (2, 'c', 9, 12)
        1 (3, 'c', 4, 6)
        2 (2, 'c', 1, 7)
        3 (3, 'b', 9, 12)
        4 (2, 'b', 4, 6)
        5 (3, 'b', 1, 7)
        6 (3, 'a', 9, 12)
        7 (2, 'a', 4, 6)
        8 (3, 'a', 1, 7)

    .. note::
        This can be directly used in ``pytest.mark.parametrize`` function.

        >>> @pytest.mark.unittest
        ... class TestTestingGeneratorFunc:
        ...     @pytest.mark.parametrize(*tmatrix({
        ...         'a': [2, 3],
        ...         'e': ['a', 'b', 'c'],
        ...         ('b', 'c'): [(1, 7), (4, 6), (9, 12)],
        ...     }))
        ...     def test_tmatrix_usage(self, a, e, b, c):
        ...         print(a, e, b, c)
    """
    mode = MatrixMode.loads(mode)

    # Create internal key mapping for processing
    key_map = {}
    final_names = []
    final_values = {}
    for ki, (key, value) in enumerate(ranges.items()):
        kname = f'key-{ki}'
        key_map[kname] = key
        final_names.append(kname)
        final_values[kname] = value

    # Extract all parameter names from the ranges
    names = []
    for key in ranges.keys():
        if isinstance(key, str):
            names.append(key)
        elif isinstance(key, tuple):
            for k in key:
                names.append(k)

    # Create appropriate generator based on mode
    if mode == MatrixMode.MATRIX:
        generator = MatrixGenerator(final_values, final_names)
    elif mode == MatrixMode.AETG:
        generator = AETGGenerator(
            final_values, final_names, rnd=seed,
            pairs=list(progressive_for(final_names, min(level, len(names)))),
        )
    else:
        raise ValueError(f'Invalid mode - {mode!r}.')  # pragma: no cover

    # Generate test cases and transform them to final format
    pairs = []
    for case in generator.cases():
        _v_case = {}
        for name in final_names:
            key = key_map[name]
            if isinstance(key, str):
                _v_case[key] = case[name]
            elif isinstance(key, tuple):
                for ikey, ivalue in zip(key, case[name]):
                    _v_case[ikey] = ivalue

        pairs.append(tuple(_v_case[name] for name in names))

    return names, pairs
